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Sanofi Group Senior Genetics Scientist in Framingham, Massachusetts

Position Overview:

The Translational Sciences Group in Sanofi strives to generate scientific knowledge that translates into transformative therapies for patients with unmet medical needs. Translational Sciences is building a world-class Bioinformatics & Genetics team that is passionate to contribute to the discovery and development of novel therapeutics for patients. Translational Sciences Bioinformatics & Genetics team is seeking highly motivated statistical geneticist to join the multidisciplinary team to apply novel statistical genetics approaches to various internal, external and consortia genotype & phenotype datasets. The successful candidate would contribute to various drug discovery and development projects for a number of indications of interest to Sanofi. The successful candidate will have the training, knowledge and expertise in the application of advanced approaches on a diverse set of data derived from number of genetics studies to develop actionable hypotheses. The successful candidate would have the ability to learn and acquire new techniques and methodologies. The selected candidate is expected to contribute to and lead projects and develop analytical strategies for the identification of novel therapeutic targets, the discovery of predictive biomarkers for patients’ stratification, and analysis of genotype and phenotype data to assess drug discovery and development. The successful candidate would have key strengths in data integration strategies as key to building and progressing pipeline for patients. This exciting role will afford talented statistical geneticist the opportunity to translate their data-integration and analytical abilities into novel actionable hypotheses.

Key Responsibilities:

  • The statistical geneticist will develop and use extensive databases of genotype and phenotype data to develop methods and implement analysis that address questions around associating risk of developing a disease, progressing, or risk of therapy failure.

  • Work collaboratively within a diverse team of Clinical Scientists, Computational Biologists, and disease experts in multiple therapy areas.

  • Integrate and lead hypotheses generation from genetics and diverse datasets by employing sound statistical genetics and computational biology approaches, for various aspects of drug discovery and development, in a pan-therapeutic manner.

  • Bring in datasets from external and internal sources to help develop internal resources for various analytical approaches involving genetics.

  • Develop and apply innovative statistical genetics approaches to understand complex disease conditions using multi-dimensional –omics and clinical data.

  • Contribute to data projects to Identify candidate therapeutic targets and biomarkers for indications of interest, through integrated analysis of high-throughput molecular data, real-world data and clinical phenotypes.

  • Collaborate with wet-lab and computational scientific teams and help the group champion projects from discovery to early clinical development.

Basic Qualifications:

  • Ph.D. in Statistical Genetics, Biostatistics, or Computational Biology.

  • Experience analyzing genotype-phenotype relationships in human populations.

  • Proficiency in analyzing large data sets with R/Bioconductor, Python, or SQL.

  • Working knowledge of Linux/HPC and shell scripting.

  • Knowledge of Jupyter notebooks and working in Cloud computing environment.

  • Knowledge of drug discovery and development is a plus.

  • 1 year of experience in a drug discovery and development context or biotechnology context on working with diverse datasets.

  • The ability to manage multiple projects in parallel, communicate clearly and effectively and build open and collaborative relationships is essential.

  • Strong interested in biology and caring for developing novel therapeutic intervention strategies for patients with unmet disease conditions, and an ability to liaise with scientists from multiple therapy areas to help define and address biological questions.

Preferred Qualifications:

  • Ability to develop, benchmark and apply predictive algorithms to identify novel biomarkers, dissect gene/disease relationships and generate hypotheses.

  • Proficiency in biostatistics, linear/non-linear regression models, dimensionality reduction, clustering, AI/machine learning methods, is a plus.

  • Exposure to and ability to work with data from UK Biobank, DisGeNet, & FinnGen.

  • Excellent written and oral communication skills.

  • Excellent interpersonal and team skills.

  • Self-driven and ability to well in interdisciplinary teams.

  • Experienced in communicating genetics insights and presenting concepts to a diverse audience.

Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.

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At Sanofi diversity and inclusion is foundational to how we operate and embedded in our Core Values. We recognize to truly tap into the richness diversity brings we must lead with inclusion and have a workplace where those differences can thrive and be leveraged to empower the lives of our colleagues, patients and customers. We respect and celebrate the diversity of our people, their backgrounds and experiences and provide equal opportunity for all.

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